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Expectations Shocks and the Macroeconomy

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Macroeconomic Survey Expectations

Part of the book series: Palgrave Texts in Econometrics ((PTEC))

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Abstract

Survey expectations are used in vector autoregressive models (VARs) to analyse the inter-relationships between expectations and macroeconomic fluctuations. Exogenous (or structural) expectations shocks are identified by using one of the identification schemes reviewed in this chapter, which include short-run restrictions, and selecting shocks to maximize the contribution to the forecast-error variance decomposition of certain variables. In some cases expectations data can be used to capture ‘anticipatory effects’ (as in the fiscal foresight literature) and counter the non-fundamentalness problem. Uncertainty can also be used in place of first-moment expectations in VARs to analyse the relationship between uncertainty and the macroeconomy.

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Notes

  1. 1.

    The assumption that the structural shocks u t can be recovered from the ε t need not hold. Problems arise if the data generating process shocks are non-fundamental: see Sect. 9.3.

  2. 2.

    Recall that \(\widetilde {B}\) is lower triangular.

  3. 3.

    See, for example, Bachmann et al. (2013), Baker et al. (2016), and Girardi and Reuter (2017).

  4. 4.

    It is worth remarking that the ECB SPF does provide rolling density forecasts at the longer horizons. For example, López-Pérez (2016) uses the one- and two-year horizon rolling density forecasts of the ECB SPF to analyse whether survey participation depends on uncertainty, and whether ignoring—or controlling for—sample selection affects the estimated relationship between uncertainty and GDP growth expectations.

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Authors and Affiliations

  1. ICMA Centre, Henley Business School, University of Reading, Wheatley, UK

    Michael P. Clements

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  1. Michael P. Clements
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Clements, M.P. (2019). Expectations Shocks and the Macroeconomy. In: Macroeconomic Survey Expectations. Palgrave Texts in Econometrics. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-97223-7_9

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  • DOI: https://doi.org/10.1007/978-3-319-97223-7_9

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  • Publisher Name: Palgrave Macmillan, Cham

  • Print ISBN: 978-3-319-97222-0

  • Online ISBN: 978-3-319-97223-7

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